Research Methods: Data Quality Research Research is the exploration of the unknown. Done by gathering data (information) Thus, quality of data is important ? Reliability ? Validity ? Generalizability Quality Check #1: Reliability Reliability: measure is free of irrelevant influences but all measures include error Error can be from: ? Low precision or incorrect data entry ? variations in the state (mood) of: ? The participant ? The experimenter ? The environment Improving Reliability: ? Be thorough and careful ? increases precision ? Use a constant scripted procedure (protocol) ? Experimenter is more reliable ? Measure something that is important' ? Participant will be more engaged ? Aggregation (averaging things) ? Random errors cancel each other out Types of reliability: ? Internal consistency reliability ? All questions measure the same construct ? Inter-rater reliability ? Scorers (raters) agree on test results ? Test-retest reliability ? Same result with same person at different time Quality Check #2: Validity Validity: how much your measure captures what you think it does A measure must be reliable to be valid, but can be reliable without being valid. Example: a pregnancy test Construct Validity: ? Construct: theory or idea about a psychological attribute ? We want our measure to assess the construct ? To determine a measure's construct validity: ? Give your measure and many others ? Examine: ? Convergent Validity: your measure is related to things theorized to be related to the construct ? Divergent Validity: your measure is unrelated to things theorized to be unrelated to the construct. Quality Check #3: Generalizability Generalizability: how much a measure or results applies in other situations (to other people, when given at a different time, etc.) Validity & Reliability are really questions of a measure's generalizability Issues of Generalizability: ? Biggest concern is generalizing across people (to whom do the results apply?) ? Problems with college students (as participants) ? Gender Bias ? Shows vs. No Shows ? Cohort Effects ? Ethnic Diversity
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